We verify the effectiveness of Figure REF  (b) architecture in Table REF  (g vs. h).
As MSTR considers multiple semantics with two suggested deformable modules, it is important to find suitable decoder architecture which can effectively merge the semantics [1]}.
According to the possible combination ways when merging three kinds of semantics, various types of decoder architecture can be candidates for the decoder architectures (described in Appendix).
In our Appendix, we empirically verify that Figure REF  (b) architecture shows the most powerful and robust performance across all datasets.
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